Study of microstructure evolution of magnesium alloy cylindrical part with longitudinal inner ribs during hot flow forming by coupling ANN-modified CA and FEA

Abstract

Hot flow forming (HFF) is a promising forming technology to manufacture thin-walled cylindrical part with longitudinal inner ribs (CPLIRs) made of magnesium (Mg) alloys, which has wide applications in the aerospace field. However, due to the thermo-mechanical coupling effect and the existence of stiffened structure, complex microstructure evolution and uneven microstructure occur easily at the cylindrical wall (CW) and inner rib (IR) of Mg alloy thin-walled CPLIRs during the HFF. In this paper, a modified cellular automaton (CA) model of Mg alloy considering the effects of deformation conditions on material parameters was developed using the artificial neural network (ANN) method. It is found that the ANN-modified CA model exhibits better predictability for the microstructure of hot deformation than the conventional CA model. Furthermore, the microstructure evolution of ZK61 alloy CPLIRs during the HFF was analyzed by coupling the modified CA model and finite element analysis (FEA). The results show that compared with the microstructure at the same layer of the IR, more refined grains and less sufficient DRX resulted from larger strain and strain rate occur at that of the CW; various differences of strain and strain rate in the wall-thickness exist between the CW and IR, which leads to the inhomogeneity of microstructure rising firstly and declining from the inside layer to outside layer; the obtained Hall-Petch relationship between the measured microhardness and predicted grain sizes at the CW and the IR indicates the reliability of the coupled FEA-CA simulation results.

Keywords

• Magnesium alloy cylindrical part with longitudinal inner ribs
• Hot flow forming
• Microstructure evolution
• Artificial neural network
• Cellular automaton
• Finite element